Company

Technology

FullstackEngineerJR(Backend+AI)

$6000–9000k ~AI est. Buenos Aires, Argentina CONTRACT Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Entry candidates.

The Brief

“Fullstack Engineer JR (Backend + AI). Skills: Backend Development, AI Development, API Endpoints, LLM Inference. Build API endpoints. Write DRF serializers”

What You'll Achieve.

Ship production code

Industry & Context.

Technology
Problems you'll solve

Debugging; Troubleshooting

What They're Looking For.

Must Have

Solid Python fundamentals, Familiarity with web APIs, Comfort with Git, Experience with relational database, Comfortable working with AI-based tools, Genuine curiosity about AI/ML, Ability to debug AI-generated code

Nice to Have

Django or Flask experience, React/TypeScript exposure, Familiarity with Docker, Experience with vector databases, Deployed project you can demo

What You'll Do.

Write DRF serializers

Extend AI agent capabilities

Write async task workers

Build distributed RQ worker logic

Debug distributed RQ worker logic

Improve test coverage

Ship frontend features

Build React/TypeScript components

Diagnose hallucinations

Fix retrieval failures

How You'll Work.

Team & Collaboration

Work with team

Process & Methodology

Agile

Full Job Description

## Description Role Overview We are looking for a motivated Junior Fullstack Engineer with a strong backend focus who is eager to build great products and grow alongside a team that embraces cutting-edge technology. You write clean, thoughtful code, care about building reliable systems, and are genuinely curious about how AI development tools (like Cursor or Claude) can make you a faster, better developer from day one. ## Key Responsibilities Build API endpoints — write DRF serializers and viewsets serving data to a React frontend, working with complex models (JSONFields, custom managers, mixin patterns). Extend AI agent capabilities — add new tools to agents; work on context engineering, and retrieval systems. Write async task workers — build and debug distributed RQ worker logic covering document parsing (PDF, Excel, PowerPoint) and LLM inference pipelines. Improve test coverage — write pytest tests with real database fixtures, mock external APIs, and catch N+1 query issues. Ship frontend features — build React/TypeScript components wired to TanStack Query, styled with SCSS Modules; work with rich text, interactive charts, and virtualized tables. Debug AI output — diagnose and fix hallucinations and retrieval failures in agent pipelines. ## Technical Requirements Required Solid Python fundamentals — classes, tracebacks, data structures, without over-relying on AI autocomplete. Familiarity with web APIs: HTTP methods, JSON serialization, request/response cycles. Comfort with Git: branching, rebasing, resolving merge conflicts. Experience with at least one relational database: SQL queries and basic schema design. Comfortable working with AI-based tools like Cursor, Claude Code, etc. Genuine curiosity about AI/ML — LLM API usage, a RAG pipeline, or serious experimentation beyond chatting with ChatGPT. Ability to debug AI-generated code — shipping broken AI output is worse than writing it yourself. Nice to Have Django or Flask experience. React/TypeScript exposure, ev

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